Feasibility and Acceptability of Web-Based Structured Oral Examinations for Postgraduate Certification: Mixed Methods Preliminary Evaluation
Bibliographic record
Abstract
Background The COVID-19 pandemic disrupted postgraduate certification examinations globally. The Colleges of Medicine of South Africa continued hosting certification examinations through the pandemic. This was achieved by effecting a rapid transition from in-person to web-based certification examinations. Objective This formative evaluation explored candidates’ acceptability of web-based structured oral examinations (SOEs) hosted via Zoom (Zoom Communications Inc). We also reported the audiovisual quality and technical challenges encountered while using Zoom and candidates’ overall experience with these examinations conducted during the early part of the COVID-19 pandemic. Additionally, performance in web-based certification examinations was compared with previous in-person certification examinations. Methods This mixed methods, single-arm evaluation anonymously gathered candidates’ perceptions of web-based SOE acceptability, audiovisual quality, and overall experience with Zoom using a web-based survey. Pass rates of web-based and previous in-person certification examinations were compared using chi-square tests, with a Yates correction. A thematic analysis approach was adopted for qualitative data. Results Between June 2020 and June 2021, 3105 candidates registered for certification examinations, 293 (9.4%) withdrew, 2812 (90.6%) wrote, and 2799 (99.9%) passed, and 1525 (54.2%) were invited to a further web-based SOE. Examination participation was 96.2% (n=1467). During the first web-based examination cycle (2020), 542 (87.1%) of 622 web-based SOE candidates completed the web-based survey. They reported web-based SOEs as fair (374/542, 69%) and adequately testing their clinical reasoning and insight (396/542, 73.1%). Few would have preferred real patient encounters (173/542, 31.9%) or in-person oral examinations (152/542, 28%). Most found Zoom acceptable (434/542, 80%) and fair (396/542, 73.1%) for hosting web-based SOEs. SOEs resulted in financial (434/542, 80%) and time (428/542, 79%) savings for candidates. Many (336/542, 62%) supported the ongoing use of web-based certification examinations. Only 169 technical challenges in using Zoom were reported, which included connectivity-related issues, poor audio quality, and poor image quality. The thematic analysis identified 4 themes of positive and negative experiences related to web-based SOE station design and content, examination station environment, examiner-candidate interactions, and personal benefits for candidates. Our qualitative analysis identified 10 improvements for future web-based SOEs. Candidates achieved high pass rates in web-based certification examinations in 2020 (1583/1732, 91.39%) and 2021 (850/1067, 79.66%). These were significantly higher (2020: N=8635; χ21=667; P<.001; 2021: N=7988; χ21=178; P<.001) than the previous in-person certification examination pass rate of 58.23% (4030/6921; 2017-2019). Conclusions Web-based SOEs conducted by the Colleges of Medicine of South Africa during the COVID-19 pandemic were well received by candidates, and few technical difficulties were encountered while using Zoom. Better performance was observed in web-based examinations than in previous in-person certification examinations. These early findings support the ongoing use of this assessment method.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.134 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".